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ICSE 2022
Sun 8 - Fri 27 May 2022
Wed 11 May 2022 04:05 - 04:10 at ICSE room 3-even hours - Recommender Systems 1 Chair(s): Alessio Ferrari
Wed 11 May 2022 13:05 - 13:10 at ICSE room 5-odd hours - Recommender Systems 2 Chair(s): Gabriele Bavota

Code review is essential for assuring system quality in software engineering. Over decades in practice, code review has evolved to be a lightweight tool-based process focusing on code change: the smallest unit of the development cycle, and we refer to it as Modern Code Review (MCR). MCR involves code contributors committing code changes and code reviewers reviewing the assigned code changes. Such a reviewer assigning process is challenged by efficiently finding appropriate reviewers. Confronting such challenges, recent studies propose automated code reviewer recommendation (CRR) approaches. These approaches are often evaluated on open-source projects and obtain promising performance.

However, the code reviewer recommendation systems are not widely used on proprietary projects, and most current reviewer selecting practice is still manual or, at best, semi-manual. No previous work systematically evaluated the effectiveness of these approaches and compare each other on proprietary projects in practice. In this paper, we performed a quantitative analysis of typical recommendation approaches on proprietary projects in Tencent. The results show an imperfect performance of these approaches on proprietary projects and reveal practical challenges like the ``cold start problem''. To better understand practical challenges, we interviewed practitioners about the expectations of applying reviewer recommendations to a production environment. The interview involves the current systems’ limitations, expected application scenario, and information requirements. Finally, we discuss the implications and the direction of practical code reviewer recommendation tools.

Wed 11 May

Displayed time zone: Eastern Time (US & Canada) change

04:00 - 05:00
04:00
5m
Talk
Predicting the Objective and Priority of Issue Reports in Software Repositories
Journal-First Papers
Maliheh Izadi Sharif University of Technology, Kiana Akbari Sharif University of technology, Abbas Heydarnoori Sharif University of Technology
Link to publication DOI Pre-print Media Attached
04:05
5m
Talk
Code Reviewer Recommendation in Tencent: Practice, Challenge, and Direction
SEIP - Software Engineering in Practice
Qiuyuan Chen Zhejiang University, Dezhen Kong Zhejiang University, Lingfeng Bao Zhejiang University, Chenxing Sun Tencent, Xin Xia Huawei Software Engineering Application Technology Lab, Shanping Li Zhejiang University
Pre-print Media Attached
04:10
5m
Talk
Using Deep Learning to Generate Complete Log Statements
Technical Track
Antonio Mastropaolo Università della Svizzera italiana, Luca Pascarella Università della Svizzera italiana (USI), Gabriele Bavota Software Institute, USI Università della Svizzera italiana
Pre-print Media Attached
04:15
5m
Talk
Modeling Review History for Reviewer Recommendation: A Hypergraph Approach
Technical Track
Guoping Rong Nanjing University, YiFan Zhang Nanjing University, Lanxin Yang Nanjing University, Fuli Zhang Nanjing University, Hongyu Kuang Nanjing University, He Zhang Nanjing University
Pre-print Media Attached
04:20
5m
Talk
ShellFusion: Answer Generation for Shell Programming Tasks via Knowledge Fusion
Technical Track
Neng Zhang School of Software Engineering, Sun Yat-sen University, Chao Liu Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, Christoph Treude University of Melbourne, Ying Zou Queen's University, Kingston, Ontario, David Lo Singapore Management University, Zibin Zheng School of Data and Computer Science, Sun Yat-sen University
DOI Pre-print Media Attached
04:25
5m
Talk
CLEAR: Contrastive Learning for API Recommendation
Technical Track
Moshi Wei York University, Nima Shiri harzevili York University, Yuchao Huang Institute of Software Chinese Academy of Sciences, Junjie Wang Institute of Software at Chinese Academy of Sciences, Song Wang York University
Pre-print Media Attached
13:00 - 14:00
Recommender Systems 2Technical Track / NIER - New Ideas and Emerging Results / SEIP - Software Engineering in Practice at ICSE room 5-odd hours
Chair(s): Gabriele Bavota Software Institute, USI Università della Svizzera italiana
13:00
5m
Talk
Better Modeling the Programming World with Code Concept Graphs-augmented Multi-modal Learning
NIER - New Ideas and Emerging Results
Martin Weyssow DIRO, Université de Montréal, Houari Sahraoui Université de Montréal, Bang Liu DIRO & Mila, Université de Montréal
Pre-print Media Attached
13:05
5m
Talk
Code Reviewer Recommendation in Tencent: Practice, Challenge, and Direction
SEIP - Software Engineering in Practice
Qiuyuan Chen Zhejiang University, Dezhen Kong Zhejiang University, Lingfeng Bao Zhejiang University, Chenxing Sun Tencent, Xin Xia Huawei Software Engineering Application Technology Lab, Shanping Li Zhejiang University
Pre-print Media Attached
13:10
5m
Talk
Recommending Good First Issues in GitHub OSS Projects
Technical Track
Wenxin Xiao School of Computer Science, Peking University, Hao He Peking University, Weiwei Xu School of Computer Science and Technology, Soochow University, Xin Tan Beihang University, China, Jinhao Dong Peking University, Minghui Zhou Peking University, China
Pre-print Media Attached
13:15
5m
Talk
Modeling Review History for Reviewer Recommendation: A Hypergraph Approach
Technical Track
Guoping Rong Nanjing University, YiFan Zhang Nanjing University, Lanxin Yang Nanjing University, Fuli Zhang Nanjing University, Hongyu Kuang Nanjing University, He Zhang Nanjing University
Pre-print Media Attached
13:20
5m
Talk
ShellFusion: Answer Generation for Shell Programming Tasks via Knowledge Fusion
Technical Track
Neng Zhang School of Software Engineering, Sun Yat-sen University, Chao Liu Zhejiang University, Xin Xia Huawei Software Engineering Application Technology Lab, Christoph Treude University of Melbourne, Ying Zou Queen's University, Kingston, Ontario, David Lo Singapore Management University, Zibin Zheng School of Data and Computer Science, Sun Yat-sen University
DOI Pre-print Media Attached
13:25
5m
Talk
Using Deep Learning to Generate Complete Log Statements
Technical Track
Antonio Mastropaolo Università della Svizzera italiana, Luca Pascarella Università della Svizzera italiana (USI), Gabriele Bavota Software Institute, USI Università della Svizzera italiana
Pre-print Media Attached

Information for Participants
Wed 11 May 2022 04:00 - 05:00 at ICSE room 3-even hours - Recommender Systems 1 Chair(s): Alessio Ferrari
Info for room ICSE room 3-even hours:

Click here to go to the room on Midspace

Wed 11 May 2022 13:00 - 14:00 at ICSE room 5-odd hours - Recommender Systems 2 Chair(s): Gabriele Bavota
Info for room ICSE room 5-odd hours:

Click here to go to the room on Midspace